The book provides an understanding of the technical aspects of swarm intelligence algorithms, techniques and their potential use in IoT-based applications.
Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.
Nearly all aspects of resource optimization using the IoT are covered in the 18 chapters of this book including energy management monitoring, data management and mining technologies, healthcare data analytics, and wireless sensor networks. In addition, there are introductory chapters on IoT with swarm intelligence, as well as a fundamental overview of different algorithms and performance optimization for swarm intelligence.
Audience
Researchers and industry engineers in computer science, software engineering, artificial intelligence, Internet of Things.
From the Back Cover
The book provides an understanding of the technical aspects of swarm intelligence algorithms, techniques and their potential use in IoT-based applications.
Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.
Nearly all aspects of resource optimization using the IoT are covered in the 18 chapters of this book including energy management monitoring, data management and mining technologies, healthcare data analytics, and wireless sensor networks. In addition, there are introductory chapters on IoT with swarm intelligence, as well as a fundamental overview of different algorithms and performance optimization for swarm intelligence.
Audience
Researchers and industry engineers in computer science, software engineering, artificial intelligence, Internet of Things.
About the Author
Abhishek Kumar gained his PhD in computer science from the University of Madras, India in 2019. He is assistant professor at Chitkara University and has more than 80 publications in peer-reviewed international and national journals, books & conferences His research interests include artificial intelligence, image processing, computer vision, data mining and machine learning.
Pramod Singh Rathore has a MTech in Computer Science & Engineering from the Government Engineering College Ajmer, Rajasthan Technical University, Kota India, where he is now an assistant professor. He has more than 60 papers, chapters, and a book to his credit and his research interests are in networking cloud and IoT.
Vicente García Díaz obtained his PhD in Computer Science in 2011 at the University of Oviedo, Spain where he is now an associate professor in the School of Computer Science. He has published more than 100 publications and his research interests include domain-specific languages, e-learning, decision support systems.
Rashmi Agrawal obtained her PhD in Computer Applications in 2016 from Manav Rachna International University Faridabad, India, where she is now a professor in the Department of Computer Applications. Her research area includes data mining and artificial intelligence and she has published more than 65 publications to her credit.
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